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cover of episode 314 - Fluke - Brian Klaas (rebroadcast)

314 - Fluke - Brian Klaas (rebroadcast)

2025/5/26
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You Are Not So Smart
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Brian Kloss: 我认为广岛被摧毁而非京都，直接原因是19年前一对夫妇的旅行。这个例子说明，看似微小的个人经历，能在历史的重大关头产生意想不到的影响。我们倾向于认为重大事件背后必有重大原因，但事实往往是，随机事件在复杂系统中相互作用，最终导致了难以预测的结果。这种认知偏差导致了阴谋论的产生，人们总是试图寻找更深层次的原因，而忽略了偶然性的作用。我研究坏人做坏事，这让我开始思考事情发生的原因，我发现历史并非由预定的计划或强大的力量所驱动，而是充满了偶然和随机的因素，这些因素在复杂系统中相互作用，最终塑造了历史的走向。因此，我们应该更加关注那些看似微不足道的细节，因为它们可能在未来的某个时刻产生巨大的影响。 Brian Kloss: 我认为我们应该认识到，历史事件并非完全由必然性所决定，偶然性在其中扮演了重要的角色。例如，一颗小行星的撞击，一个微小的天气变化，都可能对历史产生深远的影响。因此，我们应该更加谦逊地看待历史，认识到我们对历史的控制是有限的。我们应该更加关注那些看似微不足道的细节，因为它们可能在未来的某个时刻产生巨大的影响。我们应该更加开放地接受新的信息，并不断地修正我们的认知。只有这样，我们才能更好地理解历史，并从中吸取教训。

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This chapter explores the story of Henry and Mabel Stimson's trip to Kyoto in 1926 and its unforeseen impact on the decision of where to drop the atomic bombs in 1945. It introduces the concept of proportionality bias, which leads people to believe that major events must have major causes, while often overlooking the significant role of random events.
  • Henry Stimson's 1926 trip to Kyoto influenced his decision to spare the city from atomic bombing.
  • Proportionality bias is the tendency to assume that significant events have similarly significant causes.
  • Random events can have profound and unpredictable consequences.

Shownotes Transcript

In this episode we sit down with Brian Klaas, author of Fluke, and get into the existential lessons and grander meaning for a life well-lived (once one finally accepts the power and influence of randomness, chaos, and chance). In addition, we learn not to fall prey to proportionality bias - the tendency for human brains to assume big, historical, or massively impactful events must have had big causes and/or complex machinations underlying their grand outcomes. It’s one of the cognitive biases that most contributes to conspiratorial thinking and grand conspiracy theories, one that leads to an assumption that there must be something more going on when big, often unlikely, events make the evening news. Yet, as Brian explains, events big and small are often the result of random inputs in complex systems interacting in ways that are difficult to predict.

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